From ffc3a7f28ba780c2a3a660c1aa3c99bb6bfe0e8c Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Thu, 14 May 2026 17:14:39 +0000 Subject: [PATCH] Deployed a0627aa to develop in en with MkDocs 1.6.1 and mike 2.2.0 --- en/develop/freqai-configuration/index.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/en/develop/freqai-configuration/index.html b/en/develop/freqai-configuration/index.html index d385c5e5f..f0acee73d 100644 --- a/en/develop/freqai-configuration/index.html +++ b/en/develop/freqai-configuration/index.html @@ -2459,7 +2459,7 @@ will cause the algorithm to fail in live/dry mode. In order to add generalized f df['%%*'] -Any dataframe column prepended with %% in feature_engineering_*() is treated as a training feature, just the same as the above % prepend. However, in this case, the features are returned back to the strategy for FreqUI/plot-dataframe plotting and monitoring in Dry/Live/Backtesting
Datatype: Depends on the feature created by the user. Please note that features created in feature_engineering_expand() will have automatic FreqAI naming schemas depending on the expansions that you configured (i.e. include_timeframes, include_corr_pairlist, indicators_periods_candles, include_shifted_candles). So if you want to plot %%-rsi from feature_engineering_expand_all(), the final naming scheme for your plotting config would be: %%-rsi-period_10_ETH/USDT:USDT_1h for the rsi feature with period=10, timeframe=1h, and pair=ETH/USDT:USDT (the :USDT is added if you are using futures pairs). It is useful to simply add print(dataframe.columns) in your populate_indicators() after self.freqai.start() to see the full list of available features that are returned to the strategy for plotting purposes. +Any dataframe column prepended with %% in feature_engineering_*() is treated as a training feature, just the same as the above % prepend. However, in this case, the features are returned back to the strategy for FreqUI/plot-dataframe plotting and monitoring in Dry/Live/Backtesting
Datatype: Depends on the feature created by the user.
Please note that features created in feature_engineering_expand() will have automatic FreqAI naming schemas depending on the expansions that you configured (i.e. include_timeframes, include_corr_pairlist, indicators_periods_candles, include_shifted_candles). So if you want to plot %%-rsi from feature_engineering_expand_all(), the final naming scheme for your plotting config would be: %%-rsi-period_10_ETH/USDT:USDT_1h for the rsi feature with period=10, timeframe=1h, and pair=ETH/USDT:USDT (the :USDT is added if you are using futures pairs). It is useful to simply add print(dataframe.columns) in your populate_indicators() after self.freqai.start() to see the full list of available features that are returned to the strategy for plotting purposes.